glot500_fr_gsd_ca_ancora

This model is a fine-tuned version of cis-lmu/glot500-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0617
• Precision: 0.9815
• Recall: 0.9833
• F1: 0.9824
• Accuracy: 0.9845

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0939	1.0	1724	0.0716	0.9785	0.9803	0.9794	0.9821
0.0617	2.0	3448	0.0617	0.9815	0.9833	0.9824	0.9845

Framework versions

• Transformers 4.48.2
• Pytorch 2.5.1+cu124
• Datasets 3.3.0
• Tokenizers 0.21.0